Behavioral considerations for effective time-varying electricity prices

Abstract

Wholesale prices for electricity vary significantly due to high fluctuations and low elasticity of short-run demand. End-use customers have typically paid flat retail rates for their electricity consumption, and timevarying prices (TVPs) have been proposed to help reduce peak consumption and lower the overall cost of servicing demand. Unfortunately, the general practice is an opt-in system: a default rule in favor of TVPs would be far better. A behaviorally informed analysis also shows that when transaction costs and decision biases are taken into account, the most cost-reflective policies are not necessarily the most efficient. On reasonable assumptions, real-time prices can result in less peak conservation of manually controlled devices than time-of-use or critical-peak prices. For that reason, the trade-offs between engaging automated and manually controlled loads must be carefully considered in time-varying rate design. The rate type and accompanying program details should be designed with the behavioral biases of consumers in mind, while minimizing price distortions for automated devices.

The Efficiency and Distributional Effects of Alternative Residential Electricity Rate Designs

“…Note that while the nature of efficient energy prices is well understood, the optimal strategies for eliciting efficient customer response are less clear. Schneider and Sunstein (2017) highlight how transaction costs and behavioral biases impact the optimal type and frequency of price notifications.…”

Restructuring Revisited Part 2: Coordination in Electricity Distribution Systems

“…This paper evaluates the first program to expose residential consumers to hourly real-time pricing (RTP). Some scholars have argued that, due to transaction costs and attention limits, consumers might prefer and even respond more acutely to less-variable prices (Schneider & Sunstein, 2017). If this is the case and consumers are charged according to a marginal-cost based tariff, competitive entities (for example, aggregators) will ultimately find value in offering contracts, hedging strategies, and demand management to help consumers reduce costs and minimize the attention they must pay to electricity prices.…”

Building Social License for Automated Demand-Side Management—Case Study Research in the Swiss Residential Sector

“…Alternatively, DSM can be automated via (i) home energy management systems (HEMS) that households set up and (ii) other means such as direct load control (DLC), where a utility can switch on and off certain devices depending on the grid needs [12]. Considering the low response rate and/or reduced response in the long term to dynamic tariffs [13][14][15][16], automated DSM is increasingly considered as a more effective option to activate flexibility compared to pricing tariffs [17]. Indeed, response to price signals is limited since electricity consumption is inelastic and dependent upon timing of human activities rather than prices [15,18], and its end-users are also subject to inattention and decision fatigue [13].…”

“…Considering the low response rate and/or reduced response in the long term to dynamic tariffs [13][14][15][16], automated DSM is increasingly considered as a more effective option to activate flexibility compared to pricing tariffs [17]. Indeed, response to price signals is limited since electricity consumption is inelastic and dependent upon timing of human activities rather than prices [15,18], and its end-users are also subject to inattention and decision fatigue [13]. On the utility side, automated DSM is recognised as a more "reliable and economic operation of power systems and electricity markets" [19] and a way to integrate renewable energies [20,21].…”